Evaluating Nutrient-Based Indices against Food- and Diet-Based Indices to Assess the Health Potential of Foods: How Does the Australian Health Star Rating System Perform after Five Years?

Assessing the Validity of Front-of-Pack Nutrition Labels for Evaluating the Healthiness of Mediterranean Food Choices: A Global Comparison

In response to growing public health concerns, governments worldwide have implemented various nutrition labelling schemes to promote healthier eating habits. This study aimed to assess the consistency and effectiveness of these labels in an out-of-home context, specifically focusing on restaurant, hospitality, and institutional food service settings. In total, 178 different dishes from Spain were analysed using labels from the Mazocco method, the UK's traffic light system, the Health Star Rating (Australia), Nutri-Score (France), multiple traffic lights (Ecuador), and warning labels (Chile and Uruguay). The results demonstrated a generally low level of agreement among these labels (K < 0.40), indicating notable variability and a lack of consensus, which could hinder consumers' ability to make informed food choices in out-of-home settings. Nutri-Score classified the highest number of dishes as unhealthy (38%). This study underscores the need for an easy-to-understand labelling system tailored to each country's culinary and socio-cultural contexts to improve consumer decision-making in various dining environments. Future research should focus on developing and testing qualitative methods to more accurately gauge the nutritional quality of cooked dishes in diverse out-of-home settings, thereby enhancing public health outcomes. By addressing the specific needs of the home, restaurants, hospitality, and institutional food services, tailored labelling schemes could significantly improve consumers' ability to make healthier food choices.

Modifying the Health Star Rating nutrient profiling algorithm to account for ultra-processing

AIM

To modify the Australian and New Zealand Health Star Rating to account for ultra-processing and compare the alignment of the modified ratings with NOVA classifications and the current Australian Dietary Guidelines classifications of core (recommended foods) and discretionary (foods to limit).

METHODS

Data was cross-sectionally analysed for 25 486 products. Four approaches were compared to the original Health Star Rating: (1) five 'negative' points added to ultra-processed products (modification 1; inclusion approach); (2) ultra-processed products restricted to a maximum of 3.0 Health Stars (modification 2; capping approach); (3 and 4) same approach used for modifications 1 and 2 but only applied to products that already exceeded 10 'negative' points from existing Health Star Rating attributes (modifications 3 and 4, respectively; hybrid approaches). Alignment occurred when products (i) received <3.5 Health Stars and were NOVA group 4 (for NOVA comparison) or discretionary (for Dietary Guidelines comparison), or (ii) received ≥3.5 Health Stars and were NOVA groups 1-3 or core.

RESULTS

All Health Star Rating modifications resulted in greater alignment with NOVA (ranging from 69% to 88%) compared to the original Health Star Rating (66%). None of the modifications resulted in greater alignment to the Dietary Guidelines classifications overall (69% to 76%, compared with 77% for the original Health Star Rating), but alignment varied considerably by food category.

CONCLUSIONS

If ultra-processing were incorporated into the Australian and New Zealand Health Star Rating, consideration of ultra-processing within the broader dietary guidance framework would be essential to ensure coherent dietary messaging to Australians.

An ecological reorientation of the Codex Alimentarius Commission could help transform food systems

The Codex Alimentarius Commission (Codex) has a substantial influence over the structure and operation of food systems by setting international standards that affect the composition, structure and labelling of food. Despite the dual mandates of Codex to protect public health and ensure fair practices in food trade, food systems are increasingly unhealthy and unsustainable. An ecological reorientation of the decision-making elements that influence how Codex sets food standards-particularly mandates, governance and risk assessment-could help transform food systems towards the UN Sustainable Development Goals.

Switches in food and beverage product purchases can reduce greenhouse gas emissions in Australia

Switching between similar food and beverage products may reduce greenhouse gas emissions (GHGe). Here, using consumer data linked to 23,550 product-specific GHGe values, we estimated annual GHGe attributable to product purchases consumed at home in Australia and calculated reductions from specific switches. Potential changes to mean Health Star Rating, mean energy density and the proportion of ultraprocessed foods purchased were assessed. Approximately 31 million tonnes of GHGe were attributable to products consumed at home in 2019, the three highest contributors of GHGe being 'meat and meat products' (49%), 'dairy' (17%) and 'non-alcoholic beverages' (16%). Switching higher-emission products for 'very similar' lower-emission products could reduce total emissions by 26%. Switches to 'less similar' lower-emission products could lead to a 71% reduction. Switches had little impact on the average Health Star Rating, energy density of purchases and proportion of ultraprocessed foods purchased. Directing manufacturing and marketing towards lower-environmental-impact products and signposting such options to consumers are key.

Extent of alignment between the Australian Dietary Guidelines and the NOVA classification system across the Australian packaged food supply

AIMS

The Australian Dietary Guidelines are currently being revised and ultra-processed foods have been identified as a high priority action area. To better understand how well the current Dietary Guidelines align with level of processing classifications, the aim of this study was to assess the alignment between the Australian Dietary Guidelines and the NOVA classification system for classifying the healthiness of packaged foods.

METHODS

Data were sourced from the Australian FoodSwitch dataset, which included 28 071 packaged food and beverage products available in major Australian supermarkets in 2022. Products were classified as (i) core or discretionary (Australian Dietary Guidelines) and (ii) non-ultra-processed or ultra-processed (NOVA). Agreement between the two systems (core vs. non-ultra-processed and discretionary vs. ultra-processed) was evaluated using the kappa statistic.

RESULTS

There was 'moderate' agreement (κ = 0.41, 95% CI: 0.40-0.42) between the Australian Dietary Guidelines and the NOVA system, with 69.8% of products aligned across the two systems. Alignment was more common for discretionary foods (80.6% were ultra-processed) than core foods (59.9% aligned were not-ultra-processed). Food categories exhibiting the strongest levels of alignment included confectionary, foods for specific dietary use, and egg and egg products. Discordance was most common for convenience foods, sugars, honey and related products, and cereal and grain products.

CONCLUSIONS

Despite moderate alignment between the Australian Dietary Guidelines and NOVA, the discordance observed for almost one-third of products highlights the opportunity to develop recommendations for ultra-processed foods within the guidelines to advise Australians how these foods should be considered as part of a healthy diet.

Monitoring health and nutrition claims on food labels in Brazil

Introduction

The monitoring of nutrition and health claims on food and beverage labels has been proposed by international and national organizations because it can collaborate with the development of public policies to regulate food labeling and marketing strategies. One way of carrying out this monitoring is by using data collected by private companies.

Objective

To compare information on nutrition and health claims available in a commercial database of a private company that monitors the launch of new foods and beverages in Brazilian food retailers with information on those same claims manually coded by trained research assistants.

Methods

This is a cross-sectional observational study using a data sample of newly launched food and beverages available at a commercial database from 2018 to 2021. We compared the information on health and nutrition claims available on the commercial dataset with reliable information on the same nutrition and health claims manually coded by trained research assistants using a tested taxonomy to classify such claims. We used Gwet's Kappa AC1 with 95% CI and percentage agreement to compare both data sources and calculated sensitivity and specificity of the compared data.

Results

A total of 6,722 foods and beverages were analyzed. Mintel-GNPD presented 36.28% (n = 2,439) of nutrition claims, while in the trained researchers' coding, it was 33.73% (n = 2,267). We found a prevalence of 5.4% (n = 362) for health claims in Mintel-GNPD and 10.8% (n = 723) in the researchers' coding. All subcategories of nutrition and health claims showed high agreement (Kappa >0.81). Health claims presented kappa = 0.89 with 33.7% sensitivity and 98.0% specificity while nutrition claims showed kappa = 0.86 with 92.9% sensitivity and 92.5% specificity.

Conclusion

Nutrition and health claims showed high agreement, with great results in nutrition claims, indicating that Mintel-GPND is suitable for monitoring such claims on food and beverage packaging in Brazil. Additionally, our findings show a high prevalence of nutrition and health claims on food packages launched in the Brazilian food retail, highlighting the need to monitor these to develop public policies to regulate food marketing on packaging in Brazil.

Comparing product healthiness according to the Health Star Rating and the NOVA classification system and implications for food labelling systems: An analysis of 25 486 products in Australia

We investigated the extent of alignment between 'healthiness' defined by a food classification system that classifies foods and beverages primarily by their nutrient composition, the Health Star Rating (HSR) and a system that considers only the degree of processing of the product, the NOVA classification system. We used data for 25 486 products contained within the George Institute for Global Health's Australian 2022 FoodSwitch Dataset. Agreement between the two systems in the proportion of products classified as 'healthier' (HSR ≥3.5 or NOVA group 1-3) or 'less healthy' (HSR <3.5 or NOVA group 4) was assessed using the κ statistic. There was 'fair' agreement (κ = 0.30, 95%CI: 0.29-0.31) between both systems in the proportion of all products classified as healthier or less healthy. Approximately one-third (n = 8729) of all products were defined as 'discordant', including 34.3% (n = 5620) of NOVA group 4 products with HSR ≥3.5 (commonly convenience foods, sports/diet foods, meat alternatives, as well as products containing non-sugar sweeteners) and 34.1% (n = 3109) of NOVA group 1-3 products with HSR <3.5 (commonly single-ingredient foods such as sugars/syrups, full-fat dairy and products specially produced to contain no ultra-processed ingredients). Our analysis strengthens the evidence for the similarities and differences in product healthiness according to a nutrient-based classification system and a processing-based classification system. Although the systems' classifications align for the majority of food and beverage products, the discordance found for some product categories indicates potential for confusion if systems are deployed alongside each other within food policies.

Food additives and PAHO's nutrient profile model as contributors' elements to the identification of ultra-processed food products

The NOVA classification system categorizes foods according to the extent and purpose of industrial processing. Ultra-processed food products (UPF) are frequently composed of excessive amounts of sugars, salt, oils, and fats, and cosmetic additives designed to make them palatable and/or appealing. We aimed to describe the presence of critical nutrients in excess and cosmetic additives in packaged foods and beverages and to evaluate the proportion of UPF that can be correctly identified through the presence of critical nutrients in excess or the presence of cosmetic additives in food products. A total of 9851 items available in Brazilian supermarkets containing lists of ingredients and nutrition facts panels were analyzed. Cosmetic additives and critical nutrients in excess, according to Pan American Health Organization (PAHO)'s nutrient profile model, were assessed. All food items were categorized into the four NOVA classification groups. Relative frequencies of items with at least one critical nutrient in excess and one type of cosmetic additive were estimated. For UPF, 82.1% had some cosmetic additive, and 98.8% had some cosmetic additive or a nutrient in excess. This combined criterion allowed the identification of 100.0% of sweet cookies, salted biscuits, margarine, cakes and sweet pies, chocolate, dairy beverages, and ice cream. Combining the presence of cosmetic additives and the PAHO's nutrient profile model contributes to the identification of UPF.

A novel food processing-based nutrition classification scheme for guiding policy actions applied to the Australian food supply

Unhealthy diets are a leading risk factor for non-communicable diseases and negatively impact environmental sustainability. Policy actions recommended to address dietary risk factors, such as restrictions on marketing and front-of-pack labelling, are informed by nutrition classification schemes (NCSs). Ultra-processed foods are associated with adverse population and planetary health outcomes, yet the concept is rarely incorporated in nutrition classification schemes for policy actions. This study aims to develop a novel food processing-based nutrition classification scheme for guiding policy actions. A secondary aim is to validate the scheme by classifying food and beverage items in the Australian food supply (face validity) and comparing them to the classifications of existing NCSs (convergent validity). Two versions of a model were developed, classifying foods and beverages in two steps, first using the NOVA classification system and secondly by applying upper thresholds for added free sugars and sodium, producing a binary output of either healthy or unhealthy. All food and beverage items (n = 7,322) in a dataset combining the Australian Food Composition Database (AUSNUT 2011-2013) and Mintel's Global New Product Database (2014-2019) were classified using the two models. The same dataset was also classified by the Health Star Rating system (HSR), The Australian Dietary Guidelines (ADGs), The Pan American Health Organization's Nutrient Profile Model (PAHO NPM), and the NOVA classification scheme, and pairwise agreement between all NCSs and the two models was determined (using Cohen's Kappa coefficient). A higher proportion of food categories consistent with dietary patterns that are associated with positive health outcomes, such and fruits, vegetables, and eggs were classified as healthy. And the clear majority of food categories consistent with dietary patterns associated with adverse health outcomes, such as confectionery, snack foods, and convenience foods were classified as unhealthy. The two versions of the model showed substantial agreement with NOVA and the PAHO NPM, fair agreement with the ADGs and slight to moderate agreement with the HSR system. A model NCS combining level of processing and nutrient criteria presents a valid alternative to existing methods to classify the health potential of individual foods for policy purposes.

Are Front-of-Pack Nutrition Labels Influencing Food Choices and Purchases, Diet Quality, and Modeled Health Outcomes? A Narrative Review of Four Systems

Front-of-Pack Nutrition labels (FOPNLs) aim to improve consumers' food purchases and prompt product reformulation by the food and beverage industry. Despite their widespread use, the effectiveness of FOPNL in achieving these goals is still a matter of debate. This review has gathered 65 original studies exploring the performances of four widely used FOPNLs (Multiple Traffic Light, Warning signs, Nutri-Score and Health Star Rating). Although FOPNLs have been associated with healthier food purchases, the magnitude of improvements was small and dependent on study settings. Any associated health effects were modeled rather than observed. None of the four FOPNLs clearly outperformed the other ones on any outcome. Few studies dealt with the impact of FOPNL on product reformulation. Some of those studies, but not all, found small reductions in energy, sodium, sugar and saturated fat content of foods in some food categories. Although global trends point to a small favorable effect of FOPNL, this conclusion is subject to caution since the evidence is inconsistent and comes from a wide variety of contexts and study designs. There remain numerous research gaps, notably with regard to the optimal characteristics of FOPNLs, the durability of FOPNL effects on consumer behaviors, and any possible unexpected consequences.

Validation of the Thumbs food classification system as a tool to accurately identify the healthiness of foods

The Thumbs food classification system was developed to assist remote Australian communities to identify food healthiness. This study aimed to assess: (1) the Thumbs system’s alignment to two other food classification systems, the Health Star Rating (HSR) and the Northern Territory School Canteens Guidelines (NTSCG); (2) its accuracy in classifying ‘unhealthy’ (contributing to discretionary energy and added sugars) and ‘healthy’ products against HSR and NTSCG; (3) areas for optimisation. Food and beverage products sold between 05/2018 and 05/2019 in fifty-one remote stores were classified in each system. System alignment was assessed by cross-tabulating percentages of products, discretionary energy and added sugars sold assigned to the same healthiness levels across the systems. The system/s capturing the highest percentage of discretionary energy and added sugars sold in ‘unhealthy’ products and the lowest levels in ‘healthy’ products were considered the best performing. Cohen’s κ was used to assess agreement between the Thumbs system and the NTSCG for classifying products as healthy. The Thumbs system classified product healthiness in line with the HSR and NTSCG, with Cohen’s κ showing moderate agreement between the Thumbs system and the NTSCG (κ = 0·60). The Thumbs system captured the most discretionary energy sold (92·2 %) and added sugar sold (90·6 %) in unhealthy products and the least discretionary energy sold (0 %) in healthy products. Modifications to optimise the Thumbs system include aligning several food categories to the NTSCG criteria and addressing core/discretionary classification discrepancies of fruit juice/drinks. The Thumbs system offers a classification algorithm that could strengthen the HSR system.

Nutrition Classification Schemes for Informing Nutrition Policy in Australia: Nutrient-Based, Food-Based, or Dietary-Based?

Background

Policy makers are increasingly using nutrition classification schemes (NCSs) to assess a food's health potential for informing nutrition policy actions. However, there is wide variability among the NCSs implemented and no standard benchmark against which their contrasting assessments can be validated.

Objectives

This study aimed to compare the agreement of nutrient-, food-, and dietary-based NCSs in their assessment of a food's health potential within the Australian food supply, and examine the conceptual underpinnings and technical characteristics that explain differences in performance.

Methods

A dataset combining food compositional data from the Mintel Global New Products Database and the Australian Food Composition Database (AUSNUT 2011-2012) (n = 7322) was assembled. Products were classified by 7 prominent NCSs that were selected as representative of one or other of 1) nutrient-based NCSs [the Chilean nutrient profile model (NPM), Health Star Rating (HSR), Nutri-Score, the WHO European Region's NPM (WHO-Euro NPM), and the Pan American Health Organization's (PAHO) NPM]; 2) food-based NCS (NOVA), and 3) dietary-based NCS [Australian Dietary Guidelines (ADGs)].

Results

The PAHO NPM classified the lowest proportion (22%) of products as "healthy", and the HSR the highest (63%). The PAHO NPM, NOVA, WHO-Euro NPM, and the Chilean NPM classified >50% of products as "unhealthy," and the ADGs, HSR, and Nutri-Score classified <50% of products as "unhealthy." The HSR and Nutri-Score had the highest pairwise agreement (κ = 0.7809, 89.70%), and the PAHO NPM and HSR the lowest (κ = 0.1793, 53.22%). Characteristics of NCSs that more effectively identified ultraprocessed and discretionary foods were: category-specific assessment, the classification of categories as always "healthy" or "unhealthy," consideration of level of food processing, thresholds for "risk" nutrients that do not penalize whole foods; and no allowance for the substitution of ingredients.

Conclusions

Wide variation was observed in agreement of the assessment of a food's health potential among the NCSs analyzed due to differing conceptual underpinnings and technical characteristics.

What are the benefits and risks of nutrition policy actions to reduce added sugar consumption? An Australian case study

OBJECTIVE

This study aimed to critically analyse Australia's current and proposed policy actions to reduce added sugar consumption. Over-consumption of added sugar is a significant public health nutrition issue. The competing interests, values and beliefs among stakeholders mean they have disparate views regarding which policy actions are preferable to reduce added sugar consumption.

DESIGN

Semi-structured interviews using purposive, snowball sampling and policy mapping. Policy actions were classified by two frameworks: NOURISHING (e.g. behaviour change communication, food environment and food system) and the Orders of Change (e.g. first order: technical adjustments, second order: reforming the system, third order: transforming the system).

SETTING

Australia.

PARTICIPANTS

Twenty-two stakeholders from the food industry, food regulation, government, public health groups and academia.

RESULTS

All proposed and existing policy actions targeted the food environment/behaviour change; most were assessed as first-order changes, and reductionist (nutrient specific) in nature. Influences on policy actions included industry power, stakeholder fragmentation, government ideology/political will and public pressure. Few stakeholders considered potential risks of policy actions, particularly of non-nutritive sweetener substitution or opportunity costs for other policies.

CONCLUSIONS

Most of Australia's policy actions to reduce added sugar consumption are reductionist. Preferencing nutrient specific, first-order policy actions could reflect the influence of vested interests, a historically dominant reductionist orientation to nutrition science and policy, and the perceived difficulty of pursuing second- or third-order changes. Pursuing only first-order policy actions could lead to 'regrettable' substitutions and creates an opportunity cost for more comprehensive policy aimed at adjusting the broader food system.

Evaluating intake levels of nutrients linked to non-communicable diseases in Australia using the novel combination of food processing and nutrient profiling metrics of the PAHO Nutrient Profile Model

PURPOSE

To investigate intake levels of nutrients linked to non-communicable diseases in Australia using the novel combination of food processing and nutrient profiling metrics of the PAHO Nutrient Profile Model.

METHODS

Dietary intakes of 12,153 participants from the Australian Health Survey (2011-12) aged 2 + years were evaluated. Food items reported during a 24 h recall were classified using the NOVA system. The Pan-American Health Organization Nutrient Profile Model (PAHO NPM) was applied to identify processed and ultra-processed products with excessive content of critical nutrients. Differences in mean intakes and prevalence of excessive intakes of critical nutrients for groups of the population whose diets were made up of products with and without excessive content in critical nutrients were examined.

RESULTS

The majority of Australians consumed daily at least three processed and ultra-processed products identified as excessive in critical nutrients according to the PAHO NPM. Individuals consuming these products had higher intakes of free sugars (β = 8.9), total fats (β = 11.0), saturated fats (β = 4.6), trans fats (β = 0.2), and sodium (β = 1788 for adolescents and adults; β = 1769 for children 5-10 years; β = 1319 for children aged < 5 years) (p ≤ 0.001 for all nutrients) than individuals not consuming these foods. The prevalence of excessive intake of all critical nutrients also followed the same trend.

CONCLUSION

The PAHO NPM has shown to be a relevant tool to predict intake levels of nutrients linked to non-communicable diseases in Australia and, therefore, could be used to inform policy actions aimed at increasing the healthiness of food environments.

Plant-based dietary quality and depressive symptoms in Australian vegans and vegetarians: a cross-sectional study

Plant-based dietary patterns (vegan and vegetarian) are often considered 'healthy' and have been associated with broad health benefits, including decreased risk of obesity and ill health (cardiovascular disease, blood glucose and type II diabetes). However, the association between plant-based diets and mood disorders such as depression remains largely equivocal. This cross-sectional study of 219 adults aged 18-44 (M=31.22, SD=7.40) explored the associations between an estimate of overall plant-based diet quality and depression in vegans (n=165) and vegetarians (n=54). Overall plant-based diet quality was associated with depressive symptoms in vegans and vegetarians F(1, 215)=13.71, p<0.001 accounting for 6% of the variation in depressive symptoms. For those without depression, higher diet quality was protective against depressive symptoms F(1, 125)=6.49, p=0.012. Conversely, for those with depression no association with diet quality was found F(1, 89)=0.01, p=0.963. These findings suggest that a high-quality plant-based diet may be protective against depressive symptoms in vegans and vegetarians. In line with emerging research between food and mental health, higher-quality dietary patterns are associated with a reduced risk of depressive symptoms. Given the rapidly increasing rate of vegan and vegetarian food products within Australia, understanding the potential mechanisms of effects through which a plant-based diet may influence depressive symptoms is required.

Empirico-inductive and/or hypothetico-deductive methods in food science and nutrition research: which one to favor for a better global health?

Scientific research generally follows two main methods: empirico-inductive (EI), gathering scattered, real-world qualitative/quantitative data to elaborate holistic theories, and the hypothetico-deductive (HD) approach, testing the validity of hypothesized theory in specific conditions, generally according to reductionist methodologies or designs, with the risk of over simplifying the initial complexity empirically perceived in its holistic view. However, in current food and nutrition research, new hypotheses are often elaborated from reductionist data obtained with the HD approach, and aggregated to form (ultra)reductionist theories, with no application of EI observations, limiting the applicability of these hypotheses in real life. This trend and the application of the EI method are illustrated as regards with the global health issue through the examples of food classifications/scoring, clinical studies, the definition of a sustainable diet, the "matrix effect"-related hypothesis, the concept of healthy core metabolism, and obesity prevention within the perspective of social sciences. To be efficient for producing food and nutritional data appropriable by the society, it finally appears that not only both approaches are necessary, starting with the EI method then the HD one, but also a back and forth between the two, this being not always realized, potentially leading to confusion and misunderstanding in society.

Does the Australian Health Star Rating System Encourage Added Sugar Reformulation? Trends in Sweetener Use in Australia

Dietary risk factors, including excess added sugar intake, are leading contributors to Australia's burden of disease. An objective of the Australian Health Star Rating (HSR) system is to encourage the reformulation of packaged foods. Manufacturers may improve a product's HSR by replacing added sugar with non-nutritive sweeteners (NNS). Concerns have been raised regarding the potential substitution effects of ultra-processed foods containing NNS for whole foods, and the long-term impact this may have on population health. The aim of this study was to determine whether the implementation of the HSR system has impacted the use of added sugars and NNS in the food supply. Four product categories were used: products with no added sweetener, products containing added sugar only, products containing NNS only, and products containing a combination of added sugar and NNS. Of 6477 newly released products analyzed displaying a HSR in Australia between 2014-2020, 63% contained added sugars. The proportion of new products sweetened with added sugars increased over time, while NNS use did not, despite a higher average and median HSR for products sweetened with NNS. These findings suggest that at the current time, the HSR system may not discourage the use of added sugars in new products or incentivize the reformulation of added sugar with NNS. As the health risks of NNS are questioned, increased reformulation of products with NNS to reduce the presence of added sugar in the food supply may not address broader health concerns. Instead, supporting the promotion of whole foods and drinks should be prioritized, as well as policy actions that reduce the proliferation and availability of UPFs.

Australian Consumers Are Willing to Pay for the Health Star Rating Front-of-Pack Nutrition Label

The Australia and New Zealand Ministerial Forum on Food Regulation has supported the recommendations set out in the 2019 Health Star Rating System Five Year Review Report. Specifically, the forum supported, in principle, Recommendation 9, to mandate the Health Star Rating if clear uptake targets were not achieved while the system is voluntary. Given that mandatory labelling is being considered, it is important to investigate how much consumers value the Health Star Rating in order to understand potential consumer uptake and inform industry. The aim of this study was to assess consumers' valuation of the Health Star Rating system by analysing their willingness to pay for a packaged food product with the Health Star Rating label, utilising a double-bounded dichotomous choice contingent valuation approach. The results indicate that almost two-thirds of Australian household grocery shoppers were willing to pay more for a product with the Health Star Rating, on average up to an additional 3.7% of the price of the product. However, public health nutrition benefits associated with consumers' willingness to pay more for products with the Health Star Rating is currently limited by the lack of guarantee of the systems' accuracy. Given consumer support, a well validated and comprehensive Health Star Rating labelling system can potentially improve health outcomes, cost effectiveness and reduce environmental impacts.

Energy Density of New Food Products Targeted to Children

High dietary energy density (ED) is linked to childhood obesity and poor diet quality. The Australian Health Star Rating (HSR) system aims to assist consumers in making healthful food choices. This cross-sectional study used 2014-2018 data from the Mintel Global New Products Database to describe the ED of new food products targeted to children (5-12 years) released after the introduction of HSR and examine relationships between ED and HSR. Products were categorised by ED (low < 630 kJ/100 g, medium 630-950 kJ/100 g, high > 950 kJ/100 g) and HSR (no, HSR < 2.5 low, HSR ≥ 2.5 high). Non-parametric statistics were used to examine ED and HSR. A total of 548 products targeted children: 21% low, 5% medium, 74% high ED. One hundred products displayed an HSR: 24% low, 76% high; 53 products with both high HSR and ED. The EDs of products differed by HSR (p < 0.05), but both group's medians (HSR < 2.5: 1850 kJ/100 g, HSR ≥ 2.5: 1507 kJ/100 g) were high. A high proportion of new products had a high ED, and the HSR of these foods did not consistently discriminate between ED levels, particularly for high ED foods. Policies to promote lower ED foods and better alignment between ED and HSR may improve childhood obesity and diet quality.